<p>In order to enhance the precision of fatigue life prediction and achieve better lightweight design for electric truck frames, this paper proposes a fatigue-constrained lightweight design method for electric truck frames considering the layout of the power battery system. Firstly, a finite element model (FEM) of a truck frame is developed to calculate its static performance and free modal analysis. The accuracy of the FEM is verified through free modal experiment. Subsequently, the impact of different layouts of power battery system on the performance of the electric truck frame is analyzed, and the optimal layout scheme is determined. Based on the analysis of big data from the Internet of Vehicles, a multi-condition fatigue analysis load spectrum is constructed through real-world road load measurement experiments. The Critical Plane method is used in the time domain for high-precision prediction and analysis of the fatigue life of the electric truck frame. Finally, the size and shape of the frame are taken as the variables, the minimum mass and displacement of the frame as the objectives, and the fatigue life, modal frequency, and stress of the frame as the constraints. The optimal Latin hypercube design (OLHD) method is used to construct the sample space, and a RSM-Kriging hybrid surrogate model is established. The Elitist Non-dominated Sorting Genetic Algorithm (NSGA-II) is used for multi-objective optimization design to obtain the optimal lightweight scheme. The results demonstrate that after optimization, the frame weight is reduced by 29.2&#xa0;kg, representing a 4.46% reduction in weight and a notable lightweight effect.</p>